@article{01K4Z2VAGHK96DVD2C0AWYTCB2,
  abstract     = {{Process innovation is a crucial driver of firms' competitiveness, but difficulties in knowledge transfer make it challenging. Drawing on the ability-motivation-opportunity framework for knowledge transfer, we propose that the scale on which firms deploy AI technologies has a positive impact on the likelihood they introduce process innovations, as AI overcomes human limitations related to the ability and motivation for knowledge transfer. Moreover, we argue that this relationship will be more pronounced when there is lower opportunity for interpersonal knowledge transfer, and in particular when firms (a) have a large number of employees, (b) do not provide on-site employee training, and (c) have higher employee turnover. We use a unique combination of survey and social balance sheet data on a sample of 2268 Belgian firms. Heckman maximum-likelihood probit models and several robustness tests confirm the majority of our hypotheses. The study enriches the literature on process innovation and knowledge management, and provides important theoretical and practical insights on how and under which circumstances AI can lead to a competitive advantage.}},
  articleno    = {{103350}},
  author       = {{Standaert, Thomas and Andries, Petra}},
  issn         = {{0166-4972}},
  journal      = {{TECHNOVATION}},
  keywords     = {{Artificial intelligence,Process innovation,Knowledge,Knowledge transfer,Interpersonal interaction,ARTIFICIAL-INTELLIGENCE,FIRM PERFORMANCE,MANAGEMENT,ORGANIZATIONS,PRODUCT,MODEL,WORK,CAPABILITIES,INTEGRATION,MOTIVATION}},
  language     = {{eng}},
  pages        = {{12}},
  title        = {{Overcoming difficulties in knowledge transfer : harnessing the power of AI to drive process innovation}},
  url          = {{http://doi.org/10.1016/j.technovation.2025.103350}},
  volume       = {{149}},
  year         = {{2026}},
}

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